Prior to 2017, when each ovariole was thought to harbor just two or three FSCs, the cell autonomous effects of altered genotypes on FSC biology were ascertained by measuring the frequency of surviving marked FSC clones, defined by the presence of labeled FCs and a putative FSC, at various times after clone induction relative to control genotypes tested in parallel (Castanieto et al., 2014; Kirilly et al., 2005; O'Reilly et al., 2008; Song and Xie, 2003; Vied et al., 2012; Wang et al., 2012). Numerous genetic changes were found to reduce FSC clone survival severely. Occasionally, the normally low frequency of ovarioles containing only marked FSCs and FCs (‘all-marked’) was also elevated, indicating a genotype that markedly increased FSC competitiveness. Now that it is appreciated that there are 14–16 FSCs in distinct AP locations, associated with different instantaneous division rates and differentiation potential, and that FSCs produce EC as well as FCs (Hayashi et al., 2020; Reilein et al., 2017; Waghmare et al., 2018), the results of clonal analysis can reveal far more about the effect of a specific genotype on different aspects of FSC behavior and the net effect on FSC survival and amplification can be measured more precisely by measuring FSC numbers. Correspondingly, labeled lineages must be scored in far more detail than before to reveal that information.

We conducted an extensive series of experiments using a standard regime in order to extract comprehensive quantitative information about FSC behavior and to be able to compare results for a large number of altered genotypes among all experiments in the series. We induced GFP-labeled clones in dividing cells of young, well-fed adult females using the MARCM (Mosaic Analysis with a Repressible Cell Marker) system (Lee and Luo, 2001) with constitutive drivers (actin-GAL4 and tubulin-GAL4 together) of UAS-GFP and, where relevant, additional transgene expression. Heat-shock induction of a hs-flp recombinase transgene elicited recombination at the base of the relevant chromosome arm (using FRT recombination sites on 2L, 2R or 3R) in a fraction of FSCs (about 20%) to create homozygous recessive mutations or activate expression of a transgene (or both). After 6 or 12 days, ovarioles were dissected, labeled for 1 hr with the nucleotide analog EdU to measure cell division (for the 6d test only), fixed and stained to label all nuclei and the cell surface protein, Fasciclin 3 (Fas3). Each experiment included a variety of altered genotypes and a control with the same FRT recombination site. For each sample, GFP-labeled FC locations along the ovariole were recorded (Figure 1C,D) and complete confocal z-section stacks of the germarium were archived and analyzed to count labeled FSCs in layer 1, immediately anterior to the border of strong Fas3 staining, and in the next two anterior layers (2 and 3), as well as labeled ECs (anterior to FSCs) (Figure 1B), scoring also the number of labeled ECs and FSCs that had incorporated EdU (at 6d) (Figure 1E).

Our objective was to use the results to measure each distinguishable parameter of FSC behavior or decision-making separately (Figure 1F). Cell division over the FSC domain was measured by EdU incorporation at the earlier time-point (6d) so that sufficient FSCs of poorly competitive genotypes were still present in good numbers and hyper-competitive FSCs were not sufficiently abundant to potentially distort germarial morphology or induce secondary, non-autonomous responses. Genotype-dependent changes in the precise AP location of FSCs within the FSC domain were evident at 6d but were consistently most prominent at 12d, as were changes in the average number of FSCs present, so only the 12d results are presented. FC production was assessed quantitatively by a method we devised for measuring the probability of FC production per posterior FSC in one cycle of egg chamber budding (‘p’ in Figure 1F), using 6d samples to ensure a suitably low frequency of posterior FSCs for all genotypes. EC production was measured from 0-6d and 0-12d; it was normalized to the inferred number of anterior FSCs present during those periods.

Normal FSC behavior was reported by controls from 31 separate MARCM experiments, scoring at least 50 ovarioles in almost every case. The results were extremely similar to those deduced previously from the more limited set of multicolor and MARCM experiments that formed the basis of our current perception of FSCs (Reilein et al., 2017). The results for controls are summarized in Figure 1F and will be referenced individually later, in the context of genetic changes that alter those behaviors.

Here we note that each germarium contained an average of 3.2 marked FSCs at 6d and 3.3 marked FSCs at 12d, counting all ovarioles, including those with no labeled cells. If marked FSCs of the control genotype have no competitive advantage or disadvantage over unmarked FSCs it is expected that the average number of labeled FSCs should remain constant, as observed, and these measurements should therefore report the average number of FSCs initially labeled in each germarium (as 3.2–3.3 at 0d). When deducing FSC properties for the first time it was often important to assay ovarioles with lineages derived from a single FSC (Fox et al., 2008; Kretzschmar and Watt, 2012; Reilein et al., 2017). For example, FSC lineages with only a single candidate FSC at the time of examination were used to ascertain the location of FSCs as being in any radial location, most frequently in layer one or in layer two and occasionally in layer three (Reilein et al., 2017). Similarly, the ability of an FSC to produce both FCs and ECs was demonstrated by generating FSC lineages at very low frequency, so that most lineages originated from a single cell (Reilein et al., 2017). In the present studies we already can define FSCs by location and the labeling of over three FSCs per ovariole is advantageous because it effectively allows us to examine the fate of a larger number of FSCs for a given number of ovarioles. Initial labeling of each FSC in a germarium is theoretically independent and the chance of an FSC being labeled in any two germaria is theoretically equal, so the number of initially labeled FSCs per ovariole can be estimated to have a binomial distribution centered around 3.2–3.3 (‘0d’, red in Figure 1G). The observed distribution at 6d was quite different from the assumed starting distribution, most obviously because more than a third of ovarioles no longer included any FSCs, while the proportion of ovarioles with six or more FSCs had increased (Figure 1G), consistent with expectations for neutral competition (Jones, 2010; Reilein et al., 2017; Reilein et al., 2018). These changes were further exaggerated at 12d but full colonization of a germarium by marked cells generally takes longer (Reilein et al., 2017), so even at 12d marked FSCs remain in a minority and are competing against unmarked wild-type cells in almost all ovarioles (Figure 1G). That circumstance also applies to almost all variant genotypes investigated, ensuring that results reflect competition of marked FSCs with wild-type FSCs.

In control clones 6d after induction, the average percentage of all GFP-marked FSCs that incorporated EdU was 25.1% (n = 4753) with a pronounced gradient of labeling, declining from posterior to anterior (33.4% for layer 1, 20.0% for layer 2, and 8.2% for layer 3) (Figure 2A), similar to previous observations (Reilein et al., 2017). It had previously been observed that FSCs are rapidly lost in the absence of STAT activity, and that FSCs with excess JAK-STAT pathway activity became unusually numerous and included derivatives that incorporated EdU within the EC domain, suggesting that this pathway may affect FSC proliferation (Vied et al., 2012). However, the quantitative effect of JAK-STAT signaling on FSC division rates has not been reported. We found that only 2.4% of FSCs with either of two homozygous null stat alleles incorporated EdU (n = 336), a ten-fold reduction compared to controls (Figure 2A,B). To increase JAK-STAT activity, we expressed excess levels of the only Drosophila Janus Kinase, Hopscotch (Hop) using a UAS-Hop transgene in FSC clones (Vied et al., 2012; Xi et al., 2003), and found that 43.9% of UAS-Hop FSCs incorporated EdU (n = 1379), nearly double the rate of control FSC clones (Figure 2A,C; Figure 2—figure supplement 1). The pattern of EdU incorporation in these FSCs still showed a posterior bias, with 49.9% of layer 1, 39.8% of layer 2, and 32.1% of layer 3 UAS-Hop FSCs labeled by EdU, although the EdU indices of layer 1 and layer 3 FSCs relative to the whole FSC population were significantly different from controls (Figure 2A). These experiments demonstrated that the JAK-STAT pathway has a very strong positive, dose-responsive, cell autonomous influence on the FSC cell cycle. We also saw that labeled cells in the EC region, which normally do not divide at all, sometimes incorporated EdU (12.4%) when JAK-STAT pathway activity was elevated (Figure 2A; Figure 2—figure supplement 1B), as noted previously without quantitation (Vied et al., 2012).

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JAK-STAT pathway activity, reported by a ‘STAT-GFP’ transgene with ten tandem STAT binding sites (Bach et al., 2007), is graded from posterior to anterior over the FSC domain (Figure 2D,F), with a major ligand emanating from polar follicle cells (Vied et al., 2012). Because the JAK-STAT activity gradient runs parallel to the graded pattern of EdU labeling we wished to test whether the two gradients were causally related. To do this, we took advantage of the C587-GAL4 driver, which is expressed strongly in the anterior of the germarium and decreases in strength towards the posterior with almost no detectable expression in FCs (Reilein et al., 2017; Song et al., 2004). This pattern is roughly a mirror-image of the normal JAK-STAT signaling pathway gradient. We expressed UAS-Hop from the C587-GAL4 driver (C587>Hop), utilizing a temperature-sensitive GAL80 transgene (Zeidler et al., 2004) to restrict UAS-Hop expression temporally. After 3d at the restrictive temperature of 29C, we measured STAT-GFP fluorescence and found it to be similar in each of the three FSC layers and also over more anterior regions, indicating that the entire FSC domain now has roughly even JAK-STAT pathway activity (Figure 2E,F).

With roughly even JAK-STAT activity across the FSC region, we measured proliferation in the three FSC layers. We observed nearly identical frequencies of EdU labeling in each FSC layer of C587>Hop germaria; 38.2% of layer 1, 37.4% of layer 2, and 41.1% of layer 3 FSCs (Figure 2G,H,J). Thus, synthetically making JAK-STAT pathway activity uniform, rather than graded, eliminated the normal posterior to anterior gradient of EdU labeling.

Additionally, elevated JAK-STAT activity in the anterior of the germarium stimulated EdU incorporation in 10.4% of ECs (Figure 2H,J). In this experiment, those cells were quiescent ECs prior to increasing JAK-STAT activity with C587-GAL4 and temperature elevation. In the MARCM studies, the GFP-marked dividing cells in the EC region originated instead from marked FSCs with elevated JAK-STAT signaling. Clearly, excess JAK-STAT pathway activity can suffice to initiate cell division in the EC domain, whether the target cells were recently derived from FSCs or not. The rate of division of those cells, indicated by their EdU index, was substantially lower than for cells in the FSC domain (Figure 2J) despite similar levels of JAK-STAT pathway activity in the C587-GAL4/UAS-Hop experiment (Figure 2F), suggesting the presence of other factors restricting EC division or inertia due to prior quiescence (Spencer et al., 2013).

For comparison, we tested the effect of increasing CycE expression. In MARCM clones expressing UAS-CycE the FSC EdU index was greatly increased (Figure 2K) but we observed no EdU incorporation in the EC region. When UAS-CycE was expressed with the C587-GAL4 driver (C587>CycE) we found that the profile of EdU incorporation for FSCs remained graded with a posterior basis, contrasting with the response to UAS-Hop, although the gradient was flatter than in control FSCs, as revealed by statistically significant differences in the relative EdU index for layer one and for layer three relative to the overall EdU index (Figure 2I,J). Also, ECs remained quiescent. We conclude that graded JAK-STAT pathway activity instructs graded proliferation within the FSC domain, and that the anterior range of sufficient JAK-STAT pathway activity appears to define the anterior boundary of this critical stem cell property.

If JAK-STAT signaling were uniquely responsible for regulating the FSC proliferation gradient, then we would not expect there to be any bias in EdU incorporation, by layer, for FSC MARCM clones that have no JAK-STAT pathway activity. Though EdU incorporation was very low in stat FSC clones, it was graded; 6.5% of marked layer 1 FSCs incorporated EdU, compared to 1.5% for layer 2 and 0% for layer 3 (Figure 2A). Thus, there appear to be other influences that pattern FSC proliferation. Their magnitude is, however, hard to assess reliably from this experiment alone because stat mutant FSC cycling is very infrequent.

We therefore sought to introduce additional genetic changes onto a stat mutant background that would increase FSC proliferation in the marked MARCM lineages without themselves altering the normal graded pattern of proliferation. We found that expression of excess CycE and inactivation of upstream components of the Hippo/Yorkie pathway, Kibra and Warts (Wts), previously shown to influence FSC proliferation (Huang and Kalderon, 2014), appear to fulfill this requirement because the gradient of EdU labeling was largely unaltered (Figure 2K). When each of these three manipulations was paired with stat, the average frequency of EdU labeling roughly doubled compared to stat alone (2.4%), with 4.8% of kibra stat FSCs (n = 461), 5.2% of wts stat FSCs (n = 231), and 5.2% of stat UAS-CycE FSCs (n = 97) incorporating EdU, while kibra and UAS-CycE together increased EdU incorporation to 15.9% (n = 252) (Figure 2K). In all of these experiments, more FSCs in layer one incorporated EdU compared to the anterior layers in a pattern resembling that of normal FSCs (Figure 2K). Moreover, there were no statistically significant differences from controls in the relative EdU index of any one layer relative to the whole FSC population for these genotypes (Figure 2K) or stat alone (Figure 2A), indicating that, in the absence of graded JAK-STAT pathway activity in the marked cells, there remains a robust mechanism for imposing graded FSC proliferation. Once the source of this mechanism is identified it will be possible to test whether it contributes to graded FSC proliferation under normal conditions or is effective only in the absence of JAK-STAT pathway activity.

When scoring germaria with stat mutant clones, we observed that 96.5% of stat FSCs were found in the anterior layers of the germarium by 12d (Figure 3A). Since loss of STAT drastically reduces FSC proliferation we considered whether the location of FSCs might depend on their division rate. For example, even though there is exchange of FSCs between layers (Reilein et al., 2017), a proliferation-deficient FSC may compete less well in layer 1. When we tested other mutants that had severely impaired proliferation, including cycE and cutlet (Wang et al., 2012; Wang and Kalderon, 2009), we observed an altered distribution of FSCs with the proportion of FSCs in layer one reduced from a control value of 48.8% to 41.0% for cycE^WX hypomorphs and 43.3% for cutlet FSCs but those changes were not statistically significant and were much smaller than observed for stat mutant FSCs (Figure 3A).

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We also tested the consequences of increasing the division rate of stat mutant FSCs using the kibra, wts, and UAS-CycE manipulations. The proportion of layer 1 FSCs was 29.7% for kibra stat, wts stat, and UAS-CycE stat FSCs (‘kibra/wts/UAS-CycE stat’; average for the three aggregated genotypes), and 36.5% for kibra UAS-CycE stat FSCs, both significantly lower than for controls (49%) but higher than for stat alone (3.5%) (Figure 3A,D,E). Thus, we observed a consistent anterior bias for all FSCs lacking STAT activity, even for genotypes that permitted EdU incorporation at frequencies approaching normal values. The observation that stat mutant FSCs had a reduced anterior bias when their proliferation was enhanced also supports the hypothesis that reduced division rates selectively deplete FSCs from the fastest-dividing, posterior layer.

The signals and mechanisms that govern conversion of an FSC to an FC are largely unknown. In fact, only with recent insights into FSC organization can we measure this process independently of other factors, such as altered division rates, in order to attribute changes in FSC survival to changes in the frequency of differentiation to FCs (Figure 1F). Importantly, an FSC can become an FC at any time relative to its last division, and FSC division and differentiation can therefore potentially be regulated independently (Reilein et al., 2018). By correlating the location of labeled FSCs with recent production of FCs it was determined that all or most FCs derive directly from layer 1; in other words, only layer 1 FSCs associate with a passing germline cyst to become an FC (Reilein et al., 2017). Previous studies also found that a single founder FC produced a patch occupying 17.8% of the monolayer of an egg chamber on average, which translates to an average of 5.6 founder FCs (1/0.178) produced per cycle of egg chamber budding (Reilein et al., 2018).

We devised a method to determine the probability that a single FSC becomes an FC in one cycle of FC recruitment from our MARCM data. The germarium generally includes one stage 2b cyst and one stage three cyst contacting Fas3-positive FCs (Figure 1C,D). We call the first layer of Fas3-positive cells adjacent to the posterior face of the stage 2b germline cyst ‘immediate FCs’ to acknowledge that these cells very likely became FCs during the most recent cycle of FC allocation to a cyst (Figure 1B–D). The designation of ‘immediate FCs’ reflects a location used for scoring, with no implication of specialized properties. We can reliably score if there is no labeled immediate FC in a germarium but we cannot reliably score the number of immediate FCs. We therefore scored the presence or absence of immediate FCs in germaria with 0–3 marked posterior FSCs in 6d samples. Germaria with higher numbers of marked layer 1 FSCs almost invariably include marked immediate FCs (layer 1 FSCs become FCs at a high frequency) and are therefore not informative for calculating the frequency of conversion of a single layer 1 FSC to an FC. From 556 control germaria, across 31 MARCM experiments, we found that a layer 1 FSC has, on average, a 61.6% likelihood (p=0.616) of becoming an FC in one cycle (see Materials and methods) (Figure 3C).

The calculation method assumes that 7 of 16 FSCs divide in an average budding cycle, based on data from Reilein et al., 2018, so that the number of layer 1 FSCs available for conversion to FCs in one cycle is higher than the measured steady-state number by a factor of a half (because new FSCs will only be present on average for half the cycle) of 7/16. The average number of layer 1 FSCs measured from 31 control experiments was 7.6 (with 5.3 in layer 2 and 2.8 in layer 3; Figure 1F), so the expected yield of FCs per cycle is 7.6 (1+ 7/32)(0.616)=6.1. The result is close to the value of 5.6 calculated from founder FC clone sizes, validating the method employed to calculate the probability of FC formation per FSC.

When applying the same method to mutant genotypes, the calculations factored in measured changes in FSC division rate relative to controls because that influences the total number of FSCs available for conversion to FCs during a cycle (see Materials and methods). Using this method, we found that a stat mutant layer 1 FSC was much less likely than controls (34.2% compared to 61.6%) to produce an FC (Figure 3C). To determine if reduced FC production was dependent on FSC division rate we looked at kibra stat, wts stat, and UAS-CycE stat genotypes,. The average likelihood of an FSC becoming an FC was 25.3% for these three genotypes (aggregated), and it was 22.8% for kibra UAS-CycE stat mutant FSCs (Figure 3C–E). These experiments demonstrated that FC production from its immediate precursor, a layer 1 FSC, is greatly impaired in the absence of STAT activity and that this reduction is not related to changes in the rate of FSC division.

We also examined the consequences of increasing JAK-STAT pathway activity in a layer 1 FSC. We found that the probability of becoming an FC increased from 61.6% to 78.1% for FSCs expressing UAS-Hop (Figure 3C). To test any contribution of altered FSC division we introduced a UAS-Dacapo (UAS-Dap) transgene, encoding a CycE/Cdk2 inhibitor (Lane et al., 1996; Lehner et al., 1992). We found that 23.5% of UAS-Dap UAS-Hop FSCs incorporated EdU, a frequency similar to controls (Figure 3H). Layer 1 FSCs expressing both UAS-Hop and UAS-Dap also had a higher probability than controls of becoming FCs (76.7% vs 61.6%) (Figure 3C). Thus, both increased and decreased JAK-STAT pathway activity significantly affected the production of FCs from FSCs independent of FSC division rate, suggesting that the magnitude of pathway activity is an important factor in regulating this transition.

The proportion of FSCs in layer one depends not only on movements between FSC layers but also on the rate of depletion from layer one to form FCs. Loss of STAT activity in multiple genotypes reduced layer one occupancy even though conversion of layer 1 FSCs to FCs was reduced, suggesting that the bias towards anterior movement within the FSC domain is even stronger than measured simply by steady-state AP distribution (Figure 3A). Excess JAK-STAT pathway did not affect steady-state AP location but increased conversion of layer 1 FSCs to FCs, suggesting that there is in fact a bias towards posterior movement within the FSC domain that matches the increased conversion of layer 1 FSCs to FCs. Thus, both FSC flux into layer one and conversion of layer 1 FSCs to FCs are enhanced by increased JAK-STAT signaling and opposed by loss of JAK-STAT pathway activity.

It was previously noted that strong expression of the surface adhesion molecule Fas3, which is normally observed only in FCs, was induced in some derivatives of FSCs with elevated JAK-STAT signaling in the EC and FSC domains (Vied et al., 2012). We confirmed these observations for UAS-Hop MARCM clones, finding that 66% of germaria with labeled cells in the anterior half of the germarium (the FSC and EC domains) showed ectopic Fas3 expression at 12d after clone induction (Figure 3F). Furthermore, we observed that these cells sometimes appeared to form a crude epithelial monolayer surrounding developing germline cysts, indicative of FC behavior. Similar structures were observed in germaria where UAS-Hop was conditionally expressed using C587-GAL4 (Figure 3G). Here, 53% of germaria included some cells with ectopic Fas3 expression by 3d, increasing to 72% by 6d and 94% by 10d. Thus, high JAK-STAT pathway alone can instruct at least some aspects of the FC phenotype even in locations where FCs do not normally form.

To test whether Fas3 might be an important intermediate in the normal influence of JAK-STAT signaling on FC production we expressed excess Fas3 in kibra UAS-CycE stat mutant FSCs. We observed a doubling in layer 1 FSC to FC conversion (from 22.8% to 45.4%) (Figure 3C), suggesting that increased Fas3 expression can partially restore FC production in the absence of JAK-STAT pathway activity. The mechanisms controlling Fas3 expression and its role in supporting FC production remain to be explored more fully.

By measuring the impact of altered genotypes on each component of FSC behavior (Figure 1F) it should be possible to predict, or at least rationalize, the net effect on FSC competitive behavior in MARCM lineage analyses, measured by the proportion of ovarioles that retain marked FSCs over time, or measured more precisely by the average number of marked FSCs per ovariole (counting all ovarioles).

For FSCs and other stem cells governed by population asymmetry in which differentiation is independent of stem cell division, the rate of stem cell division is necessarily a major determinant of competitive success (Reilein et al., 2018). Excess JAK-STAT pathway activity substantially increased the FSC EdU index. Accordingly, by 12d, there were an average of 10.4 UAS-Hop FSCs per germarium (counting all ovarioles), significantly greater than the 3.3 FSCs per germarium observed in controls (Figure 3H). The proportion of ovarioles containing a marked FSC was also increased with UAS-Hop expression to 75.2% compared to 62.1% in controls (Figure 3H). When the increase in EdU index was suppressed by co-expressing UAS-Dap with UAS-Hop, the increase in FSC numbers was greatly reduced (Figure 3H).

FSC clones expressing UAS-CycE had a similar increase in the average EdU index to those expressing UAS-Hop (40.4% vs 43.9%) (Figure 2A,K) and, again, FSC numbers were increased. However, the increase was more modest for CycE overexpression, with an average of 5.6 marked FSCs per ovariole by 12d and 64.3% of ovarioles containing a marked FSC (Figure 3H). Neither UAS-CycE nor UAS-Hop significantly altered steady-state FSC AP location (Figure 3A), and while UAS-Hop promoted conversion of FSCs to FCs (Figure 3B), UAS-CycE did not (data not shown). The larger impact of increased JAK-STAT pathway activity on FSC numbers is plausibly because increased division was promoted preferentially in anterior FSC layers (Figure 2A,K), which normally do not divide as frequently and are lost directly to differentiation at a lower frequency than posterior FSCs, or because the domain of dividing cells has expanded into the EC region. It is also possible that the EdU index does not reflect division rates accurately and that the FSC division rates in response to excess CycE or excess Hop are not as similar as suggested by EdU incorporation.

When STAT activity was eliminated in FSC clones, there was an average of 0.3 stat FSCs per germarium and 25.3% of germaria retained a marked FSC after 12d (Figure 3H). These are large deficits compared to controls (3.2 FSCs, 62.1% of ovarioles), and similar to cycE partial loss of function mutants (0.5 FSCs, 29% of ovarioles), which also drastically reduce FSC proliferation. When we tested kibra stat, wts stat, and UAS-CycE stat genotypes, the average number of FSCs increased to 2.1 per germarium with 68.5% of germaria containing an FSC clone. An improved persistence of FSCs was expected but the magnitude of rescue was surprisingly large if considering only FSC division rates. This disparity was even more pronounced when examining FSC competition for kibra stat mutants expressing UAS-CycE, which had an average EdU index about 64% of wild-type. Here, the average number of marked FSCs was extremely high at 15.9 per germarium and 94% of ovarioles included marked FSCs (Figure 3E,H). The remarkable persistence and amplification of these FSCs shows that factors other than division rate are also major determinants of FSC competition. Specifically, the dramatically increased competitive success of FSCs lacking STAT activity for a given division rate very likely results from reduced conversion to FCs. Reduced conversion to FCs results from both the infrequent presence of FSCs in layer 1 (Figure 3A) and the markedly lower conversion of layer 1 FSCs into FCs when FSCs lack STAT activity (Figure 3C). The virtual sealing off of this conduit, which is normally the major route for FSC loss, allows marked FSCs to accumulate despite dividing at rates lower than their normal unmarked FSC neighbors.

Although the survival and amplification of FSCs lacking STAT activity were increased towards, and then beyond normal by relatively modest restoration of division rates, those FSCs still had much reduced physiological activity, measured by continued production of FCs, with very few ovarioles containing both FSCs and FCs (3.5% for stat, 9.5% for stat with kibra, wts or UAS-CycE, 17.0% for kibra UAS-CycE stat, compared to 42.8% for controls) (Figure 3D,E,H). Thus, interfering with the normal coordination of FSC division and conversion to FCs in response to JAK-STAT pathway activity by adding genetic modifiers of division alone led to extensive amplification of unproductive FSCs. In many of these ovarioles, egg chambers were surrounded entirely by unmarked cells and had an abnormal, elongated morphology (Figure 3E), perhaps suggestive of a deficiency in overall FC production.

When excess Fas3 was expressed in kibra UAS-CycE stat FSCs, doubling conversion of layer 1 FSCs to FCs and restoring rates of FC production towards normal values (Figure 3B), the average number of FSCs per germarium declined sharply from 15.9 to 2.4 (Figure 3H). At the same time, the percentage of ovarioles with at least one FSC at 12d declined from 94% to 59% but the proportion of ovarioles with FSCs and FCs increased from 17% to 31% (Figure 3H). The response to excess Fas3 provides further evidence of the large impact of the rate of FC production on both FSC numbers and the ability of FSCs to fulfill their physiological role. It also demonstrates that appropriate magnitudes of artificial stimulation of both FSC division and FSC differentiation to FCs can partially substitute for the normal coordination of these rates by JAK-STAT signaling to bring about roughly normal FSC behavior.

The role of Wnt signaling in regulating FSC behavior has already been examined in the context of a revised model of FSC numbers, locations and properties. A Fz3-RFP reporter demonstrated that Wnt pathway activity decreases in strength across the FSC region, in the anterior to posterior direction (Reilein et al., 2017; Wang and Page-McCaw, 2014). FSCs with a null arrow (arr) mutation to eliminate the Wnt pathway response and axin (axn) or Adenomatous Polyposis Coli (apc) mutations to constitutively activate the Wnt pathway in MARCM clones (Reilein et al., 2017), all illustrated a strong effect of higher Wnt signaling activity favoring anterior FSC locations and greater conversion to ECs; 77.6% of arr FSCs but only 15–20% of axn and apc FSCs were observed in layer 1, while 9.1 axn and apc ECs and 0.1 arr ECs were observed per germarium, compared to an average of 1.5 ECs for controls (Reilein et al., 2017).

Here we also tested the effect of reducing rather than eliminating Wnt pathway activity by expression of a UAS-dnTCF transgene (van de Wetering et al., 2002) in clones. We found that 63.0% of UAS-dnTCF FSCs were observed in layer 1 (compared to 48.8% for controls), a significant change but less pronounced than for arr FSCs, which showed a layer 1 occupancy of 79.3% across three replicates (n = 237 cells), including two additional tests not previously reported (Figure 4A). We also tested an additional axn replicate and confirmed layer one occupancy to be greatly decreased, to 20.6% at 12d. Occupancy of layer one was slightly higher (31.0%) for axn FSCs that also expressed excess CycE (Figure 4A) to increase division rates (from 7.4% to 15.3% towards control 25.0% EdU frequency (Figure 4E)), consistent with the evidence presented earlier of low division rates favoring more anterior locations.

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We also used the ‘immediate FC’ method to measure FC production. We found that arr layer 1 FSC clones had a significantly elevated probability (76.9% compared to 61.6% in controls) of becoming an FC, (Figure 4B). By contrast, reducing Wnt pathway activity with UAS-dnTCF did not increase conversion of layer 1 FSCs to FCs (52.9% probability). We also observed that FSCs with increased Wnt activity showed only a 22.4% likelihood of becoming an FC, a roughly threefold decrease from control values (Figure 4B). We therefore extend previous conclusions to surmise that the AP location of FSCs in a competitive environment of normal FSCs is altered by reduction, elimination or increases of Wnt pathway activity. By measuring the conversion of layer 1 FSCs to FCs as an independent parameter for the first time, we also found that increased Wnt pathway activity strongly reduced FC production from posterior FSCs and that only the most severe reductions in Wnt pathway activity enhanced FC production. These results suggest that the magnitude of Wnt pathway activity affects AP migration over the whole FSC domain, where Wnt signaling is graded, and that the decline of pathway activity to near zero values at the posterior margin of the FSC domain is a significant determinant of the FSC to FC transition.

To evaluate EC production from anterior FSCs, we calculated the average ratio of marked ECs per marked anterior (layer 2 or 3) FSC. We calculated this ratio for all germaria that retained at least one marked FSC, so that there was a possibility of EC production throughout the period scored. The average number of marked anterior FSCs (aFSCs) for control clones was slightly higher at 12d (2.7) than at 6d (2.2), as expected because more ovarioles lack any FSCs at 12d and are not included (Figure 1G). We took the number of marked anterior FSCs per germarium at 0d to be equal to those scored at 6d because almost all germaria have FSCs at 6d. We then estimated the average number of anterior FSCs present during the 0-12d period as the average of the number present at 0d (and measured at 6d) and the number measured at 12d.

In controls, we found that the EC/aFSC ratio was 0.55 (SE 0.30; SEM 0.01) for the period from 0-6d and 0.63 (SE 0.33; SEM 0.01) for the period from 0-12d (Figure 4D; median and other statistical measures are in Figure 4C). If ECs were produced by FSCs at a constant rate and all labeled ECs accumulated without loss, we would expect the 0-12d ratio to be double the 0-6d ratio. The observed percentage increase was much lower (15%) across 31 control tests, suggesting that marked ECs must also be lost at a significant frequency. The same inference is apparent from looking at the number of marked ECs per germarium at 6d (1.2) and at 12d (1.5) without any correction for the slightly greater number of anterior FSCs in germaria that retain FSCs at 12d (but still considering the same set of samples with at least one FSC). It appears that by 12d the number of marked ECs is at, or approaching a steady-state where the rate of production is matched by the rate of loss. This occurs when the average number of anterior FSCs (2.7) is almost double the number of marked ECs (1.5), suggesting that the rate of loss of marked ECs is greater than the rate of conversion from anterior FSCs on a per cell basis. Clearly, if this rate of EC loss applied to the whole population of over 30 ECs, far outnumbering the total of about eight anterior FSCs, there would be a severe net loss of ECs over time. We therefore deduce that the relatively high turnover that we infer for marked ECs must apply only to ECs newly-produced from FSCs and not to the bulk EC population present at the time of adult eclosion. It is certainly plausible that an FSC that moves into EC territory might indeed often return to its former FSC position or be unable to survive for long in EC territory if it does not associate with a germline cyst to receive key survival signals (Kirilly et al., 2011).

Apoptosis is observed in normal germaria at a low frequency (Pritchett et al., 2009) with the fraction of ECs undergoing apoptosis at any instant reported as 1.5% (Wang and Page-McCaw, 2018) or about 0.5% (19% of germaria, each with about 35 ECs) (Kirilly et al., 2011) by TUNEL labeling. The majority of apoptosis is observed in the neighborhood of the EC/FSC boundary. We sought to test whether the turnover of marked ECs was due to apoptosis by expressing the inhibitor of apoptosis, DIAP1 in otherwise wild-type clones. If EC turnover were reduced we might expect to see a greater number of ECs accumulating at all time points, including continued significant accumulation beyond 6d. We observed a small increase in marked EC numbers, whether measured per germarium at 6d (1.5) or 12d (1.7), or per anterior FSC at 6d (0.67) or 12d (0.78) (Figure 4D). These results suggest that apoptosis does contribute to the turnover of marked ECs but it does not appear to be the major factor, with EC production over 12d far short of doubling EC production over the first 6d. Other forms of cell death may play a role but it is perhaps most likely that an FSC that moves into the EC region frequently returns to the FSC domain.

We measured EC production from FSCs of various altered genotypes as described for controls, using the number of anterior FSCs at 6d for controls in each experiment as the best estimate of the number of anterior FSCs at 0d for all genotypes, so that the average number of anterior FSCs present during 0-6d and 0-12d could be calculated. We found that EC production was drastically reduced for arr mutant FSCs at 12d (0.11 ECs per anterior FSC compared to 0.63 for controls) and less severely at 6d (0.30 vs 0.55) (Figure 4D). The relatively high yield of ECs at 6d is likely because several ECs were produced in the first day or two before wild-type Arr protein was depleted and cell behavior was altered. Similarly, in FSCs expressing UAS-dnTCF there was a severe loss of marked ECs at 12d relative to controls (0.22 vs 0.63) but not at 6d (Figure 4D); here some time is likely required to accumulate sufficient dnTCF protein to inhibit Wnt pathway activity substantially. These data indicated that reduction, and especially loss of Wnt signaling greatly reduced the net conversion of marked anterior FSCs to ECs. This may be due to reduced conversion of anterior FSCs to ECs, increased turnover of ECs derived from FSCs, or both.

Loss of Wnt pathway activity is known to elicit apoptosis in ECs (Wang et al., 2015; Wang and Page-McCaw, 2018). We found that when we expressed UAS-DIAP1 in arr mutant FSCs, EC accumulation was increased relative to arr alone at both 6d (0.39 vs 0.30) and 12d (0.21 vs 0.11, p=0.06) but remained much below control values (Figure 4D). The continued deficit in EC accumulation for arr mutant cells expressing DIAP1 and that of cells expressing UAS-dnTCF suggests that the equilibrium of conversion between anterior FSCs and ECs is tilted strongly towards FSCs when Wnt pathway activity is reduced.

When Wnt pathway activity was increased using the axn and apc mutations we found the average ratio of ECs per anterior FSC to be 2.0 from 0-6d and 7.3 from 0-12d, revealing a greatly elevated rate of EC accumulation (Figure 4D). Again, perdurance of wild-type Axn or Apc proteins over the earliest period may account for the less dramatic rate of EC accumulation over the first 6d. The rapid addition of labeled ECs over 6-12d and the observation that FSC numbers eventually decline towards zero, leaving many labeled ECs suggest that there is little or no turnover of newly-produced ECs. Thus, any normal reversion of FSCs moving into EC locations back to FSC locations is strongly opposed by high levels of Wnt pathway activity. For all genotypes with altered Wnt pathway activity the marked cells in EC locations did not incorporate EdU and therefore do exhibit one of the key characteristics that distinguishes them as ECs rather than FSCs. We did not mark cellular processes and did not therefore ascertain whether these cells encapsulated germline cysts.

We also investigated JAK-STAT signaling and EC production dynamics. When STAT activity was eliminated, we found that EC production increased to 0.88 ECs per anterior FSC from 0-6d and 1.2 ECs per anterior FSC from 0-12d (Figure 3B), showing that the normal equilibrium between anterior FSCs and ECs was shifted significantly towards ECs, potentially by both increasing EC production and reducing EC loss.

The number of ECs initially produced from FSCs cannot be measured accurately for FSCs expressing UAS-Hop because increased JAK-STAT pathway activity sometimes induces the subsequent division of cells in the EC domain. We found that adding UAS-Dap to UAS-Hop reduced ectopic division in the EC domain from an EdU index of 12.4% to 5.9%. EC production from 0-6d was lower for UAS-Hop UAS-Dap FSC lineages than controls, suggesting some reduction in conversion to ECs (Figure 3B). The increased yield of marked cells in the EC region by 12d presumably results from division of some of those cells. These results, together with the unaltered AP distribution of FSCs with excess JAK-STAT activity and the anterior accumulation of stat mutant FSCs (Figure 3A) suggest that a certain minimal level of JAK-STAT pathway activity is required to prevent unbalanced anterior migration of FSCs and accelerated net conversion of anterior FSCs to ECs.

It has previously been reported that loss of Wnt signaling reduced FSC division by a small amount, with most measured FSCs in layer 1, while increased Wnt pathway activity, measured mostly in anterior FSCs, greatly decreased FSC proliferation, with results normalized in each case for FSC locations (Reilein et al., 2017). To examine the effects of reduced signaling more comprehensively in anterior FSCs we looked at more arr mutant samples, including those additionally expressing DIAP1, and four independent experiments where Wnt signaling was reduced by expression of dnTCF, which results in a less pronounced, but still significant, posterior shift of FSCs than complete inhibition of Wnt signaling (Figure 4A). We found that EdU incorporation was slightly reduced in all layers for FSCs lacking arr activity (26.3%, 15.3%, 4.0% for layers 1–3) or expressing dnTCF (24.9%, 15.2%, 5.4% for layers 1–3) relative to controls (33.4%, 20.0%, 8.2% for layers 1–3); the differences in layer one were statistically significant (Figure 4E). In all experiments where Wnt signaling was reduced or eliminated there was a clear posterior to anterior gradient of EdU labeling, as in normal FSCs with no statistically significant difference from controls in the relative EdU index of any one layer relative to the whole FSC population (Figure 4E).

In response to increased Wnt pathway activity, the EdU index was substantially reduced in all layers (13.7%, 4.8%, 2.8% for layers 1–3) but a posterior to anterior gradient was still evident (Figure 4E). To test the effect on graded proliferation further we combined loss of axn with UAS-CycE in an attempt to restore overall FSC proliferation towards wild-type levels. Excess CycE indeed doubled EdU labeling frequency overall (from 7.3% to 15.3%; control was 25%) and a robust posterior to anterior gradient was still evident (23.8%, 18.1%, 7.3% for layers 1–3) with no statistically significant difference from controls in the relative EdU index of any one layer relative to the whole FSC population for axn/apc or axn UAS-CycE genotypes (Figure 4E).

Finally, to assess the contribution of graded Wnt signaling to the A/P pattern of graded proliferation, we reduced Wnt signaling globally by expressing the UAS-dnTCF transgene with the C587-GAL4 driver (C587>dnTCF). As both normal Wnt pathway activity and C587-GAL4 expression decline from anterior to posterior across the FSC domain, this manipulation ought in theory to flatten or eliminate the normal Wnt gradient to produce a roughly even, low level of pathway activity. Fz3-RFP reporter expression showed that Wnt signaling was considerably reduced and was close to uniform across the three FSC layers (Figure 4F–H). Under these conditions there was very little difference in EdU incorporation in any FSC layer when compared to controls (Figure 4I). This result is consistent with the evidence from MARCM clones that graded FSC proliferation does not rely on graded Wnt signaling.

As both the JAK-STAT and Wnt signaling pathways play important roles in the regulation of FSCs, we asked whether regulation by each pathway is accomplished independently. We measured whether genetic manipulation of the Wnt pathway influenced JAK-STAT pathway activity cell autonomously by inducing GFP-positive MARCM clones that also expressed a STAT-eRFP reporter, which has STAT-responsive promoter sequences from the Socs36E gene (He et al., 2019). Reciprocal tests measured effects of JAK-STAT pathway alterations on Fz3-RFP reporter activity. In these tests, we measured the signal intensity of the reporters in marked cells relative to unmarked neighbors (Figure 5—figure supplements 1 and 2). Cells were considered neighbors if they would have been scored in the same FSC layer, and if they were captured within the same z-section during confocal imaging. Samples were examined 6d after clone induction so that all genotypes included marked cells in a full range of FSC locations.

For genotypes affecting JAK-STAT signaling components, STAT-RFP intensity was significantly altered when compared to neighbors, as expected. Reporter activity was significantly lower for stat mutant cells (42.4%, p=0.001) and was not altered in control clones (Figure 5—figure supplement 1A,B). Cells expressing UAS-Hop had STAT-RFP expression roughly twice that of normal neighbors. The stat genotype used is expected to prevent all stimulated JAK-STAT pathway activity. The measured residual RFP likely corresponds to a combination of basal reporter expression that is not dependent on JAK-STAT pathway activity and any perduring RFP that was induced before normal STAT protein and pathway activity were fully depleted during clone expansion. Taking RFP levels in stat mutant clones as the effective null condition, the change in STAT-RFP levels in UAS-Hop clones corresponds to an increase of more than two-fold in normal JAK-STAT pathway activity (roughly 160%/60% = 2.7). Neither FSCs expressing UAS-dnTCF nor those with axn mutations (together with UAS-CycE in order to increase FSC numbers) had significantly altered STAT-RFP expression suggesting that the magnitude of Wnt pathway activity does not cell autonomously affect JAK-STAT pathway signal transduction (Figure 5—figure supplement 1A,B).

For genotypes affecting Wnt signaling components, Fz3-RFP intensity was significantly altered when compared to neighbors, as expected. Reporter activity was significantly lower for arr mutant cells (39.4%, p=0.001) and for cells expressing UAS-dnTCF (63.1%, p=0.01) (Fig. S2). The null arr genotype used is expected to prevent all stimulated Wnt pathway activity (Wehrli et al., 2000), so residual RFP likely corresponds to perduring RFP and basal reporter activity. If RFP levels in arr mutant clones are taken as the effective null condition, UAS-dnTCF expression reduced Wnt pathway activity to below 40% of normal levels (23.4% reduction in a range of 60.3% from null to normal) in MARCM FSC lineages and the measured elevation of pathway-induced Fz3-RFP levels in axn clones (169.4%, p=0.02) corresponds to a roughly two-fold increase in normal Wnt pathway activity (129.5% change compared to a normal range of 60.3%)(Figure 5—figure supplement 2A). Neither decreased (stat and kibra UAS-CycE stat) nor increased (UAS-Hop) JAK-STAT pathway activity significantly altered Fz3-RFP expression, suggesting no direct, cell autonomous effect of JAK-STAT signaling on Wnt signal transduction (Figure 5—figure supplement 2A,B).

We then asked how manipulating both pathways within the same FSC would influence FSC behavior by measuring proliferation, position, and differentiation when both JAK-STAT and Wnt signaling activity were altered in FSC clones.

Reduction or elimination of Wnt signaling alone caused a small reduction in EdU incorporation in MARCM clones (Figure 4E). It was therefore surprising that expressing UAS-dnTCF increased EdU incorporation in FSCs lacking STAT activity (from 2.4% to 4.5%). This effect was more striking in STAT-deficient genotypes with higher division rates, elevating the EdU index of FSCs with stat mutations together with kibra, wts, or UAS-CycE from an average of 4.9% to 16.2% (Figure 5A), close to the value observed for otherwise normal FSCs expressing dn-TCF (19.0%). In other words, a five-fold reduction of EdU incorporation (5% vs 25%) due to the stat kibra/wts/UAS-CycE genotype was largely suppressed when Wnt pathway was reduced by UAS-dnTCF.

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By contrast, the increased FSC division induced by increased JAK-STAT pathway activity (43.9% EdU index) was not significantly altered by addition of dnTCF (46.3%) and was only slightly reduced by loss of arr function (37.7%) (Figure 5B; Figure 5—figure supplement 3A; Figure 6). Ectopic EdU labeling in the EC region was also largely unaltered by reducing Wnt pathway activity (increasing to 16.7% from 12.4%) (Figure 5B). EdU labeling of FSCs with increased JAK-STAT pathway activity was also only slightly reduced by genetically increasing Wnt pathway activity (from an EdU index of 43.9 to 38.3% for axn UAS-Hop) to a level far above that observed for axn/apc mutant FSCs (7.3%) (Figure 5B; Figure 5—figure supplement 3B,C). Even at a lower temperature of 22C, where GAL4 and consequently UAS-Hop activities are lower, the EdU index for axn UAS-Hop FSCs was higher than control values (28.2% vs. 18.9%) and not much lower than for UAS-Hop alone (35.1%) (Figure 5—figure supplement 3D). At both temperatures the EdU index of marked cells in the EC region was higher for axn UAS-Hop than for UAS-Hop lineages (Figure 5B; Figure 5—figure supplement 3D).

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These results indicate that normal Wnt pathway activity inhibits FSC division under artificial conditions of removing STAT activity, even in locations (layer 1) where Wnt pathway activity is quite low (Figure 5A). Under otherwise normal conditions, genetically increasing Wnt pathway activity to a level that approximates or slightly exceeds the highest physiological levels observed in the germarium, strongly inhibited FSC division but this inhibition was robustly overridden by genetically increasing JAK-STAT pathway activity (Figure 5B). Thus, inhibitory actions of the Wnt pathway can be strong and dose-dependent but are strongly suppressed by JAK-STAT pathway activity under conditions when both pathways are unaltered or both are artificially elevated.

In all samples where FSCs lacked STAT activity and expressed dnTCF there was a robust posterior to anterior gradient of EdU labeling (Figure 5A). This included genotypes with overall division rates close to controls (kibra UAS-CycE stat plus UAS-dnTCF; 21.6% vs 25% control EdU index). Thus, provided overall FSC division is bolstered by excess CycE and Yki activation, there remains a roughly normal FSC proliferation gradient in the complete absence of one major graded signaling pathway (JAK-STAT) and reduction of another (Wnt).

Increased JAK-STAT activity favored conversion of layer 1 FSCs to FCs (78.1% probability) and this was further increased by loss of arr activity (90.3% for arr UAS-Hop FSCs) to a level higher than induced by Wnt signaling deficiency alone (76.9% for arr FSCs) (Figure 6A). Thus, the combination of eliminating the normally low levels of Wnt signaling and increasing the already high levels of JAK-STAT pathway in layer 1 FSCs potently accelerated and almost mandated conversion of layer 1 FSCs to FCs. Moreover, despite accelerated loss from layer one to become FCs, 87.1% of arr UAS-Hop FSCs were found in this layer, representing an enhancement of the bias seen for arr FSCs (79.3%) (Figure 6D), and further accelerating overall FC production. Expression of dnTCF did not increase the probability of layer 1 FSC to FC conversion in the presence of either increased JAK-STAT pathway activity (Figure 6A) or in FSCs lacking STAT activity (Figure 6—figure supplement 1A). Artificially increasing Wnt pathway activity in FSCs strongly inhibited conversion to FCs (21.5% probability), but this inhibition was entirely negated by increasing JAK-STAT pathway activity in axn UAS-Hop FSCs, whether tested at 25°C (Figure 6A) or 22°C (Figure 6—figure supplement 2). Thus, reducing Wnt pathway activity to zero synergized with elevated JAK-STAT pathway activity to potently drive FSCs to become FCs, while smaller decreases achieved with dnTCF were without major consequence. High JAK-STAT activity also overcame the normally strong inhibition of FC production by elevated Wnt pathway activity.

EC production was reduced for arr FSCs, increased dramatically for axn FSCs and increased less prominently for stat FSCs. Reduction of Wnt signaling with dnTCF reduced EC production alone by 12d (Figure 4D) but did not diminish the increased EC production of FSCs lacking STAT activity (Figure 6—figure supplement 1E). The effects of UAS-Hop on EC production per anterior FSC cannot be quantified accurately because some of these marked cells in the EC region divide. Nevertheless, measurement of the total number of marked ECs provides some guidance. The average number of marked cells in the EC region per germarium at 12d, which was 1.3 for controls and 3.3 for UAS-Hop lineages, was greatly reduced for arr UAS-Hop (0.07), reduced to a lesser degree for UAS-dnTCF UAS-Hop, and greatly increased for axn UAS-Hop (17.2) FSC lineages (Figure 6E,G–I), showing that EC production is still highly responsive to changes in Wnt pathway activity in both directions even when JAK-STAT pathway activity is elevated. Thus, epistasis tests reveal a primary role of Wnt signaling for differentiation decisions in anterior regions and a primary role for JAK-STAT signaling for differentiation decisions in posterior regions.

The relatively high number and persistence of FSCs lacking STAT activity despite low division rates has been noted earlier and attributed to diminished conversion to FCs. The addition of dnTCF increased EdU labeling without increasing conversion of layer 1 FSCs to FCs and might therefore be expected to increase FSC persistence. However, for stat alone or together with kibra, wts or UAS-CycE the average number of marked FSCs at 12d was not greatly altered by addition of dnTCF (0.48 vs 0.33 for stat alone, 2.0 vs 2.1 for others) (Figure 6—figure supplement 1F). The location of FSCs did, however, shift towards layer 1 (23.5% vs 3.5% for stat alone, 36.9% vs 29.7% for others) (Figure 6—figure supplement 1B–D) and this would be expected to increase FC production even for a constant rate of conversion of layer 1 FSCs to FCs. Thus, increased division of stat mutant FSCs in response to dnTCF plausibly did not increase FSC numbers because increased division was offset by a modest increase in FC production. FSCs with kibra stat and UAS-CycE were already present at saturating normal numbers (15.9) by 12d and that number was not significantly altered by the presence of UAS-dnTCF (16.9) (Figure 6—figure supplement 1F).

Elevated JAK-STAT activity increased the average FSC number to 10.4 per germarium, largely by increasing division rates (Figure 6J). EdU incorporation was only slightly reduced for arr UAS-Hop FSCs and unchanged for UAS-dnTCF UAS-Hop FSCs. However, complete Wnt pathway inhibition greatly increased FSC concentration in layer 1 (Figure 6D) and enhanced conversion from layer one to FCs (Figure 6A,F), with the net effect of drastically reducing the 12d average FSC population to 0.3 per germarium, with only 17.8% of ovarioles retaining any marked FSCs (Figure 6G,J). Wnt pathway reduction with dnTCF only modestly increased posterior accumulation of FSCs without accelerating FC production from posterior FSCs (Figure 6A,D) and resulted in 3.2 FSCs per germarium (Figure 6J). Thus, even a greatly elevated FSC division rate cannot maintain a sufficient supply of marked FSCs when they are drained by posterior flux and conversion to FCs at the high rates promoted by a combination of high JAK-STAT pathway activity and elimination of Wnt pathway activity.

With elevated Wnt signaling in UAS-Hop mutant lineages, FSC division rates remained abnormally high (UAS-Hop was largely epistatic to axn) (Figure 5B), FC production from layer 1 FSCs was roughly normal (Figure 6A) but FSCs were predominantly in anterior locations (Figure 6D), thereby reducing the overall rate of FC production relative to UAS-Hop FSC lineages. Accordingly, labeled FSCs accumulated to an even greater extent than for UAS-Hop alone and indeed exceeded the normal capacity of the germarium at 28.1 axn UAS-Hop FSCs per germarium (Figure 6H–J). Thus, changes in Wnt pathway activity profoundly altered the competitive success of FSCs with elevated JAK-STAT pathway activity by either promoting (loss of Wnt) or reducing (elevated Wnt) FC production, without significantly altering FSC division rates in either case.

The near-parallel gradients of FSC division frequency reported by EdU incorporation and JAK-STAT pathway activity, declining from posterior to anterior across the FSC domain suggested a potential causal link (Figure 7). Indeed, when the JAK-STAT pathway was globally manipulated to be uniform across the EC and FSC domains, at a level marginally higher than seen normally in posterior FSCs, all FSCs were seen to incorporate EdU at the same high frequency and even some cells in EC locations entered the cell cycle. Thus, the pattern of JAK-STAT pathway activity appears to be a key determinant of the pattern of FSC divisions (Figure 7). Moreover, the anterior border of dividing somatic cells, a key characteristic of active stem cells, appears to be set by JAK-STAT pathway activity dropping below a critical threshold.

Figure 7

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In our studies EdU was incubated with freshly dissected ovarioles for 1 hr, so the EdU index reports the fraction of cells in S phase at the time of dissection or shortly afterwards. A higher EdU index reports a higher proportion of cells in S phase, which commonly correlates with a higher rate of cycling of the cell population assayed, but it is only a quantitative measure of the rate of cell division if the length of S phase is unchanged. It is quite possible that the length of S phase may differ between FSCs in different AP locations or under different genetic conditions, so the EdU labeling indices we report provide an indication, rather than a definitive measure of FSC division rates. Thus, the uniform EdU incorporation observed when JAK-STAT signaling was made uniform may not report the true status of FSC division rates.

Additional influences on the FSC division pattern were clearly revealed in the absence of JAK-STAT pathway activity by a robust AP gradient of EdU incorporation observed in five different genotype combinations covering a range of overall FSC division rates. We cannot yet tell whether the signals responsible for that polarized behavior normally augment JAK-STAT pathway action or serve only as a latent reserve system. Graded Hh signaling strongly promotes FSC division but it declines from anterior to posterior and cannot therefore underlie the converse gradient of FSC division (Hartman et al., 2013; Hartman et al., 2010; Huang and Kalderon, 2014; Vied et al., 2012). Wnt pathway activity clearly intersects with the mechanisms that regulate FSC cell cycles but it does not appear to have a major influence on the AP pattern of FSC divisions. Under conditions of normal JAK-STAT pathway activity, increased Wnt signaling strongly inhibits FSC division but global reduction of Wnt pathway activity that drastically diminishes graded signaling, permitted a normal pattern of FSC EdU incorporation at roughly normal frequencies. Similarly, reduced Wnt pathway activity strongly increased FSC division when STAT was inactivated but those FSCs with diminished Wnt signaling still showed a normal AP gradient of EdU incorporation. A potential physiological focus of Wnt pathway influence is at the EC/FSC border where Wnt pathway activity is high and JAK-STAT pathway low. While we did not observe any ectopic cell division in the EC region in response to Wnt pathway reduction or elimination, those observations were limited by the low frequency of Wnt pathway deficient cells in EC locations and the possibility that such cells may be prone to apoptosis or other stresses. Hence, it remains possible that high Wnt pathway activity may contribute to defining the anterior border of dividing somatic cells.

Through concerted actions on two separable parameters of behavior (FSC AP location and conversion of posterior FSCs to FCs), FC production is promoted by JAK-STAT pathway activity and reduced by Wnt pathway activity, in keeping with the relative levels and gradients of these pathways in the posterior half of the FSC domain (Figure 7). Although the mechanisms for FSC to FC conversion are currently unknown, it involves association with germline cysts and the beginning of a transition to an epithelial phenotype, neither of which are apparent in the AP movements of FSCs between layers. The concerted actions of Wnt and JAK-STAT pathways on both FC production and FSC AP location are not therefore likely different manifestations of exactly the same molecular responses to signaling. The responses to loss of Wnt signaling and elevated JAK-STAT pathway activity on these behaviors were found to be additive, with that specific combination causing an extremely high rate of FC production, severely depleting the marked FSC pool. In effect, that result shows that the signaling environment posterior to layer 1 FSCs cannot support maintenance of an FSC.

EC production from anterior FSCs was strongly favored by increasing Wnt pathway activity, as noted previously (Reilein et al., 2017), and was increased by loss of JAK-STAT signaling. We also found evidence of significant turnover of wild-type ECs produced from FSCs during adulthood and the limited effects of blocking apoptosis suggest that a major component of turnover may be a return of those cells to the FSC domain. Our measurements did not separate EC production from EC turnover but it seems likely that the changes we observed in EC accumulation in response to altered Wnt and JAK-STAT signaling may be due to regulation of both processes.

By examining twin-spot products of recombination in an FSC (with complementary colors) where one daughter lineage consisted of just a single FC patch, it was possible to measure the time between division of an FSC and acquisition of FC status, revealing that an FSC can become an FC at any time after its last division (Reilein et al., 2018). Thus, for an individual FSC, division and differentiation to an FC are separate processes. That separation of fundamental stem cell activities allows the possibility of independent regulation of each process at the single-cell level. There may, nonetheless, be some systematic connections among individual, separable FSC behaviors that coordinate behavior at the single-cell level.

Our results to date suggest that most FSC behaviors are largely independent. One exception was a potentially systematic connection between division rate and AP location. We found that cycE mutant FSCs, which may have reduced division as the only direct consequence of the mutation, had a small anterior bias and that the anterior bias of stat mutant FSCs was significantly reduced when division rate was increased by elevating CycE expression or Yki activity. Changes in AP location might plausibly be caused by poorer competition of slow-dividing FSCs in the posterior layer where normal FSCs divide and become FCs at a high rate.

In contrast to the noted effect of division rate on AP location, the greatly reduced FSC to FC conversion of stat mutants was not altered by increasing division rate through additional genetic manipulations, and the increased conversion of FSCs to FCs due to elevated JAK-STAT pathway activity was not altered by reducing FSC division rates (with a Cdk2 inhibitor). Thus, the mechanisms that regulate FSC division and FSC differentiation do not appear to be robustly coupled within single cells. However, the balance between these two processes might in theory still be achieved in single stem cells if a key regulatory signal affected both division and differentiation in appropriate proportions.

The JAK-STAT pathway was found to promote both FSC division and conversion to FCs, while reducing net conversion to ECs. About 5–6 FSCs become FCs per 12 hr budding cycle, while only one fourth as many FSCs become ECs (Reilein et al., 2018). Conversion to FCs is therefore the main drain on the FSC population that mandates compensatory FSC division. Because JAK-STAT signaling stimulates both FSC division and conversion to FCs in a dose-dependent manner, there will be a tendency to maintain each FSC, without loss or amplification, even when there are stochastic or systemic changes in the strength of this pathway. Also, by instructing posterior FSCs to divide faster than anterior FSCs the generation and loss of FSCs is roughly balanced for each layer, allowing for a roughly equal dynamic exchange of FSCs between layers, rather than, for example, a net anterior to posterior flow that would make anterior FSCs systematically longer-lived. The role of JAK-STAT signaling coordinating FSC division and differentiation was evident when pathway activity was eliminated and only the division rate of stat mutant FSCs was elevated by genetic alteration of other agents (in kibra UAS-CycE stat FSCs). The consequence was a large accumulation of hyper-competitive marked FSCs that supported very little FC production (Figure 7). Graded Wnt pathway activity appears to be important for supplementing the cell autonomous coordinating activity of JAK-STAT signaling. When JAK-STAT pathway is elevated, increased FSC division is partially offset by increased FC production and marked FSCs amplify over time. FSC amplification was greatly accelerated when Wnt pathway activity was genetically increased (in axn UAS-Hop FSCs) because FSC division remained rapid but FC production was limited through FSCs adopting more anterior locations (Figure 7). By contrast, when Wnt pathway activity was eliminated (in arr UAS-Hop FSCs) the marked FSC population was drained rapidly because conversion to FCs was enhanced without markedly altering FSC division rates (Figure 7).

Although dual JAK-STAT pathway responses, supported by Wnt pathway input to FSC AP location and conversion to FCs, contribute cell autonomously to balancing FSC division and differentiation, as described above, that balance is largely exercised at the community level when stem cells are maintained by population asymmetry. Several parameters must be balanced at the community level. The average FSC division rate must be appropriate to support production of a specific number of FCs and ECs every 12 hr but this also depends on the total number of FSCs. This, in turn, appears to be defined by a specific domain or space where FSCs can reside.

A key general question is how a stem cell domain is spatially-defined. The FSC paradigm provides an example where this can be understood in terms of the distribution and influences of ligands for two major extracellular signaling pathways. Both graded JAK-STAT and Wnt pathways contribute to both borders. The anterior border is between non-dividing ECs and FSCs. Increasing Wnt pathway activity and decreased JAK-STAT pathway activity both promote FSC to EC conversion, while declining JAK-STAT signaling also limits the proliferative zone. The posterior border is between FSCs and FCs. Increased JAK-STAT and reduction of Wnt pathway activity (to zero) promote the FSC to FC transition. Thus, the graded nature of both pathways plays a crucial role in determining the A/P extent of the FSC domain and, consequently, the number of FSCs supported.

The influences of JAK-STAT and Wnt pathways were examined here as cell autonomous responses in mosaic tissues (where most cells have normal genotypes). Further experiments manipulating pathway activities globally (in all cells) may well result in a number of compensatory changes in behavior and signaling properties, and will have to be evaluated in detail to understand to what extent the size and location of the FSC domain depends on the normal magnitude and gradations of these and other pathways.

The organization of mammalian intestinal stem cells is quite similar to FSCs and Wnt signaling also plays a prominent role. There, Wnt signals derive from mesenchymal cells surrounding the crypt base and additionally from Paneth cells in the small intestine, to form a gradient (Gehart and Clevers, 2019). In collaboration with R-Spondin signals, the magnitude of Wnt signaling appears to be translated into a variety of responses, including promotion of stem cell division and the expression of a key transcription factor, Ascl2, and Ephrin signaling components, which contribute to regulating cell migration and the transition to transit-amplifying cells (Batlle et al., 2002; Gehart and Clevers, 2019; Schuijers et al., 2015; Yan et al., 2017). Whether stem cell division is patterned and whether additional spatially-restricted signals guide the development of different stem cell products remain to be explored. In the FSC paradigm the dependence of stem cells on intermediate, rather than the highest levels of Wnt signaling as in the mammalian intestine, and the use of a second major graded patterning influence may be essential adaptations to differentiation occurring at two faces of the stem cell domain.

FSCs (originally termed SSCs) were first identified by lineage studies, which noted that long-lasting lineages generally extended from roughly the mid-point of the germarium (Margolis and Spradling, 1995). The conclusions from the same study that there were just two FSCs per germarium, each with a half-life around two weeks were subsequently cited many times. However, this dogma was dramatically revised two decades later through an extensive series of lineage studies comprising three different approaches to assess the number of FSCs as 14–16, the first definitive approach to identifying precise FSC locations and a demonstration that FSCs produced ECs as well as FSCs. A key aspect of this revision was the realization that earlier studies had implicitly assumed that FSCs are long-lived and maintained by single-cell asymmetry, leading to the exclusion of the majority of FSC lineages from all analyses, necessarily leading to substantial under-estimation of FSC numbers, over-estimation of average FSC longevity and obscuring the evidence that FSCs are in fact maintained by population asymmetry. Our current picture of FSCs is supported by extensive direct evidence; recent claims supporting the original conception of FSCs (Fadiga and Nystul, 2019) were addressed, and in our opinion, refuted comprehensively (Kalderon, 2020). Nevertheless, additional evidence can always contradict, confirm or refine an existing model.

Here we have presented extensive quantitative sets of data concerning FSC division, location and differentiation. A demanding test of the FSC model is whether the aggregation of these measured parameters fits well with the measured retention, loss or expansion of FSCs of a large range of mutant genotypes, which instruct a wide range of altered behaviors. We found that this was the case, as discussed above. One or two outcomes are especially noteworthy with regard to the number and location of FSCs. When FSCs lacked STAT activity but were stimulated by additional genetic changes to divide at rates approaching normal FSCs, those kibra UAS-CycE stat FSCs were present at an average of 15.9 FSCs per germarium, including multiple cells in each FSC layer (Figure 3A,E,H). The layer 1 FSCs were clearly stem cells rather than FCs because this genotype rarely produced FCs captured in any location along the ovariole (Figure 3E). Cells in layers 2 and 3 were also clearly stem cells rather than ECs because a large fraction incorporated EdU at a given time, while ECs are naturally quiescent. The phenotype of arr mutant FSC lineages, where almost all labeled cells are in layer one or further posterior (Figure 4A) provides further evidence that layer 1 cells are stem cells because these arr mutant lineages survive almost as well as control lineages (Figure 6J). These observations provide further confirmation of our current FSC model and are clearly not consistent with either the original models postulating just two FSCs in a single layer (Fadiga and Nystul, 2019; Margolis and Spradling, 1995; Nystul and Spradling, 2007; Nystul and Spradling, 2010) or recent postulates of an intermediate model where FSCs occupy the full circumference of the germarium but only in layer 2 (Singh et al., 2018).

Some of the mutant FSC phenotypes we observed also illustrate disease-relevant situations that could arise in other stem cells with a similar organization, such as mammalian intestinal stem cells. The relevance of mutations that allow amplification of specific stem cell genotypes to cancer origins has been described previously, both within the concept of field cancerization and specifically with regard to the effect of mutations conferring increased rates of stem cell division when differentiation is not coupled to stem cell division (Frede et al., 2014; Reilein et al., 2018; Ritsma et al., 2014; Rompolas et al., 2016; Slaughter et al., 1953; Vermeulen and Snippert, 2014). In those situations, exemplified by ptc mutations activating the Hh pathway in FSCs, a mutant stem cell expands within the normal stem cell domain to provide a stable, expanded source of hyperproliferative stem cell derivatives (Huang and Kalderon, 2014; Reilein et al., 2018; Vied and Kalderon, 2009). The properties of FSCs with increased JAK-STAT signaling provide an illustration of a more potent variant of the same principle because the genetic alteration also allows expansion of the proliferative domain into more anterior EC territory. Interestingly, for FSCs there is a genetic remedy; loss of Wnt signaling encouraged differentiation of these hyperproliferative stem cells and effectively extinguished the mutant lineages. Finally, the kibra UAS-CycE stat genotype provides a strikingly different paradigm. Here, the mutant stem cells also amplify but these stem cells do so because they rarely differentiate; they are not hyper-proliferative. If these differentiation-defective stem cells eventually out-compete all normal stem cells the ability of the stem cell community to support continued production of derivative cells will be severely compromised.

1-3d old adult D. melanogaster females with the appropriate genotypes were given a single 30 min (for FRT40A and FRT42D) or 45 min (for FRT82B) heat shock at 37C, with the heat shock duration determined by the observed relative rate of recombination for different FRT sites. Afterwards, flies were incubated at 25°C, 29°C or 22°C. Higher temperature increases GAL4 activity and was used for expression of UAS-Hop when using FRT40A or FRT42D, while 22°C was also used for the axn UAS-Hop genotype to moderate activity. Flies were maintained by frequent passage on normal rich food supplemented by fresh wet yeast during the 12d experimental period. Flies were dissected at 6d and 12d. We waited until 6d to ensure that all GAL80 present in cells, prior to clone induction, would be titrated out, permitting robust GAL4 induction of UAS-GFP and any additional transgenes. The 6d time point also ensured that any marked cells are derived from FSCs, as dividing FCs marked in the heat shock would have passed through the ovariole in less than 5d.

Immediately after dissection, 6d ovaries underwent 1 hr of EdU labelling based on the protocol of the Click-iT Plus EdU Cell Proliferation Kit for Imaging (Invitrogen). Both 6d and 12d ovaries were stained for Fasciclin III (Fas3) and GFP. Ovaries were then manually separated into constituent ovarioles, and mounted using DAPI Fluoromount-G (SouthernBiotech) to stain nuclei. Ovarioles were imaged with a Zeiss LSM700 or LSM800 confocal microscope, operated in part by the Zeiss ZEN software. The entire germarium was captured in the images, as well as an average of 3–4 egg chambers. Collected images were saved as CZI files, and were later analyzed utilizing the ZEN Lite software. We aimed to image 50 germaria for every genotype in each experiment.

Flies with alleles on an FRT40A, FRT42D, or FRT82B chromosomes were used in MARCM experiments using the following genotypes:

FRT40A: yw hs-Flp, UAS-nGFP, tub-GAL4/yw; act-GAL80 FRT40A / (X)FRT40A; act >CD2>GAL4/UAS-(Y) – where X, Y combinations included: (X) – NM (Nuclear Myc, Control), cycE^WX, cutlet^4.5.43 (Y) - UAS-Hop^3W, UAS-Dap, UAS-dnTCF.

FRT42D: yw hs-Flp, UAS-nGFP, tub-GAL4/yw; FRT42D act-GAL80 tub-GAL80/FRT42D (X); act >CD2>GAL4/UAS-(Y) – where X, Y combinations included: (X) – sha (Control), ubi-GFP (Control), arr², (Y) – UAS-Hop^3W, UAS-DIAP1, Fz3-RFP.

FRT82B: yw hs-Flp, UAS-nGFP, tub-GAL4/yw; act >CD2>GAL4 UAS-GFP/UAS-(Y); FRT82B tub-GAL80/FRT82B (X) – where X,Y combinations included: (X) – NM (control), stat^85C9, stat⁰⁶³⁴⁶, axn^E77, axn^S044320, apc1^Q8apc2^D40, kibra³², kibra^del, wts^x1, UAS-Hop^3W, UAS-CycE, UAS-dnTCF, (Y) UAS-dnTCF, Fz3-RFP, STAT-RFP, including combinations of (X) elements.

All tests not involving UAS-Hop were performed at 25°C. For UAS-Hop in experiments with FRT40A or FRT42D a temperature of 29°C was required to observe strong excess JAK-STAT phenotypes, as reported previously (Vied et al., 2012) (at 29°C act-GAL80 [provided by T. Laverty, Janelia Farms] in place of tub-GAL80 on 2L, or in addition to tub-GAL80 on 2R in MARCM clone stocks were essential to suppress GFP expression in non-recombined cells). The UAS-Hop insertion is on 3R, so that clones made with FRT82B contain two copies of UAS-Hop, with tests performed at 25°C. The phenotypes due to two copies at 25°C were overlapping with those from one copy at 29°C and those data were aggregated in summary results presented. For FRT82B clones with axn and UAS-Hop on 3R the accumulation of marked cells was so high at 25°C that samples could not be scored reliably at 12d after heat shock. Consequently, additional tests for that genotype, FRT82B Hop and an FRT82B control were performed in parallel at 22°C, with results given separately from those obtained at 25°C.

1-3d old flies of the genotype C587-GAL4; UAS-X/ts-GAL80, FRT42D tub-lacZ; (Reporter)/TM6B were chosen, where UAS-X was UAS-dnTCF, UAS-CycE, or UAS-Hop, and the reporter was either STAT-GFP or Fz3-RFP. Flies were incubated at 29°C for 3d, and UAS-Hop flies were also incubated for 6d and 10d. Dissected ovaries underwent the EdU and Immunohistochemistry protocols as above, without staining for GFP. For Fz3-RFP experiments with EdU, Alexa Fluor 488 dye was used instead of 594 to avoid spectral overlap.

Ovaries were directly dissected into a solution of 15 µM EdU in Schneider’s Drosophila media (500 µl, Gibco) and incubated for one hour at room temperature. These tubes were laid on their side and rocked manually, to ensure all dissected ovaries were fully submerged. Ovaries were then fixed in 3.7% paraformaldehyde in PBS for 10 min, treated with Triton in PBS (500 µl, 0.5% v/v) for 20 min, and rinsed 2x with bovine serum albumin (BSA) in PBS (500 µl, 3% w/v) for 5 min each rinse. Ovaries were exposed to the Click-iT Plus reaction cocktail (500 µl) for EdU visualization, for 45 min. The reaction cocktail was freshly prepared prior to use, with reagents from the Invitrogen Click-iT Plus EdU Cell Proliferation Kit for Imaging, including the Alexa Fluor 594 dye. Ovaries were then rinsed 3x with BSA in PBS (500 µl, 3% w/v) for 5 min each rinse.

For experiments without EdU, ovaries were dissected directly into a fixation solution of 4% paraformaldehyde in PBS for 10 min at room temperature, rinsed 3x in PBS, and blocked in 10% normal goat serum (NGS) (Jackson ImmunoResearch Laboratories) in PBS with 0.1% Triton and 0.05% Tween-20 (PBST) for 1 hr. Monoclonal antibodies for Fas3 were obtained from the Developmental Studies Hybridoma Bank, created by the NICHD of the NIH and maintained at The University of Iowa, Department of Biology, Iowa City, IA 52242. 7G10 anti-Fasciclin III was deposited to the DSHB by Goodman, C. and was used at 1:250 in PBST. Other primary antibodies used were anti-GFP (A6455, Molecular Probes) at 1:1000 in PBST. Ovaries were incubated in primary antibodies overnight, rinsed three times in PBST, and incubated 1–2 hr in secondary antibodies Alexa-488 and Alexa-647 (ThermoFisher) at 1:1000 in PBST to label GFP and Fas3, respectively. DAPI-Fluoromount-G (Southern Biotech) was used to mount ovaries.

All germaria were imaged in three dimensions on an LSM700 or LSM800 confocal laser scanning microscope (Zeiss) and using a 63 × 1.4 N.A. lens. Zeiss ZEN software was used to operate the microscope and view images. Images were typically 700 × 700 pixels with a bit depth of 12. The scaling per pixel was 0.21 x 0.21 x 2.5 µm. The range indicator in ZEN was used to determine the appropriate laser intensity and gain. ZEN was used to linearly adjust channel intensity for dim signals to improve brightness without photobleaching samples. Images were saved as CZI files and scored directly in ZEN. DAPI and Fas3 staining were used as landmarks to guide scoring. Marked cells were considered FSCs if they were within three cell diameters anterior of the Fas3 border. Cells immediately adjacent to the border were considered to be in Layer 1, with Layers 2 and 3 in sequentially anterior positions. Anterior to the FSC niche, the EC region was roughly divided into two halves, with region 2a ECs immediately anterior to FSCs and region 1 ECs anterior to that. Germaria were also scored (Y/N) for the presence of marked FCs. For the ‘immediate FC' method tabulation, the presence of an FC immediately posterior to Layer one was also scored Y/N. For publication, images were digitally zoomed in ZEN and exported as tif files using the ‘Contents of Image Window’ function. Images were rotated in Abode Photoshop CS5 to uniformly orient the germaria.

STAT-GFP, STAT-RFP and Fz3-RFP reporter activity was quantified within ZEN software. Using the Draw Spline Contour function, an outline of a DAPI cell nuclei was traced, and the fluorescence intensity within the outline was recorded. The outline of cells not expressing the reporter strongly (anterior ECs for JAK-STAT reporters and FCs for Fz3-RFP) were used to determine background intensity and were subtracted from calculated totals. For quantification of signaling pathway gradients in experiments using C587-GAL4 the signal in germline cells of the first egg chamber was used to determine background intensity. Also, the intensity of FCs from the second or third egg chamber of each sample was used as a reference, and all intensity measurements of cells within the germarium were divided by the reference to produce a relative intensity that could be compared between samples. For quantification of individual clones, the RFP intensity of a GFP-positive cell was divided by that of a GFP-negative cell in a similar position along the A/P axis, within the same or an adjacent Z plane and an average was calculated from many such pairs to derive the percentage intensity for labeled cells relative to unlabeled cells.

All images shown are representative of at least ten examples. In most cases the number is much higher and is given explicitly where relevant for statistical analysis of outcomes. No statistical method was used to predetermine sample size but we used prior experience to establish minimal sample sizes. No samples were excluded from analysis, provided staining was of high quality. The experiments were not randomized; all samples presented as groups in the results were part of the same experiment and treated in exactly analogous ways without regard to the identity of the sample. Investigators were not blinded during outcome assessment, but had no pre-conception of what the outcomes might be. For EdU incorporation, FSC layers, Immediate FC probability tabulations, proportion of germaria with FSCs and/or FCs, the ‘N-1’ Chi-squared test method was used to calculate a Z score for determining significance between indicated genotypes, and error was reported as standard error of a proportion. To determine whether the EdU index distribution among the FSC layers of an altered genotype different from controls, we first calculated the average EdU index for all FSCs of the altered genotype, with each layer contribution weighted based on the normal distribution of FSC among layers measured in appropriate controls (for MARCM or C587-GAL4 tests). This average EdU index was then multiplied by the control EdU index for each layer to derive expected EdU indexes for each layer of an altered genotype if the EdU pattern matched controls. Finally, a chi-squared test was applied to compare observed and expected EdU indexes for each layer to determine the statistical significance of differences. For average number of FSCs, Fz3-RFP reporter intensity comparison, and EC/FSC ratio, a t-test was used to determine significance between indicated genotypes, and error was reported as standard error of the mean.

The immediate FC method was used to calculate the probability for any layer 1 FSC to become an FC in a given cycle of egg chamber budding. As layer 1 FSCs directly give rise to FC daughters (Reilein et al., 2017), this was assessed by determining the proportion of germaria that contained a marked FC immediately posterior to the FSC region, which indicated recent FC production. This was only assessed in germaria with a small number of FSCs (1-3) to reasonably deduce the likelihood for an individual FSC. As the rate of proliferation would also influence this probability, this was accounted for in the immediate FC method equation.

• Probability of a single layer 1 FSC becoming an FC in one cycle = p

• Probability of a single layer 1 FSC dividing in one cycle = q

We assume that on average FSC division occurs halfway through a cycle, such that the probability of a newly-produced FSC becoming an FC is p/2. Therefore, the total probability (P) of an FSC becoming an FC in one cycle is the sum of two probabilities: an FSC becoming an FC and an FSC dividing and the additional FSC becoming an FC.

• p=p + (1 p)*q*(p/2)

• p=p + pq/2 – p²q/2

We calculate the probability of an FSC becoming an FC by tallying the proportion of germaria (x) that do not have immediate FC daughters when a single marked layer 1 FSC is present (we assume that, on average, a single marked layer 1 FSC was present at the start of the prior cycle).

• x = 1 – (p + pq/2 – p²q/2)

• x = 1 – p – pq/2 + p²q/2

• x = 1 – (1+q/2)*p + (q/2)*p²

• 0 = (q/2)*p² – (1+q/2)*p + (1-x)

• p = [(1+q/2) +/- SQRT((-(1+q/2)²) – (4(q/2)(1-x)))]/q (using quadratic formula)

Using this equation, we can solve for p, as x and q can be tabulated from scoring data.

We also considered germaria with immediate FC daughters that have no FSCs present in layer 1, as the only possibility is that a layer 1 FSC was present at the start of the last cycle and then became an FC. These instances were incorporated into the calculation of the proportion of germaria with a single layer 1 FSC but no immediate FCs.

If 2 or 3 FSCs were present, the square or cube root of the x ratio was used, respectively. A weighted average of adjusted x ratios for germaria with 1, 2 and 3 FSCs was calculated (weighted according to the number of examples of 0–1, 2, and 3 layer 1 FSCs) and used in the formula to calculate p.

The q value was adjusted based on measured proliferation for mutants compared to controls, as well as predicted daughter cell production, which assumes that seven FSCs (out of a total of 16 FSCs) are dividing per cycle to produce 5.6 FCs and 1.4 ECs per cycle. Therefore:

q = ‘Proportion of EdU incorporation for layer 1 FSCs (mutant or control)’ / ‘average EdU incorporation of all control FSCs’ * 7/16.

The EC/aFSC ratio was calculated by dividing the number of marked ECs per germarium present at 6d or 12d by the inferred average number of marked anterior FSCs per germarium during the 0-6d or 0-12d period. The inferred average number of anterior FSCs per germarium was the average of the observed number of anterior FSCs per germarium (at 6d or at 12d) and the observed number of anterior FSCs per germarium in the control samples at 6d for that experiment (representing our best estimate of the number of marked anterior FSCs per germarium at 0d in all samples of the same experiment). In all cases, only germaria that contained at least one marked FSC (in any position) were scored in order that there was an opportunity to produce new marked ECS throughout the experimental period. Results from multiple experiments for a particular genotype were aggregated by calculating the totals for marked ECs and for the inferred average number of anterior FSCs before deriving the overall EC per anterior FSC ratio.

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

This work was supported by NIH RO1 GM079351 to DK. We thank Aaron Choi, Amy Reilein, Jamie Little, Jianhua Huang, Haoran Liu and Diana Kim for research assistance, Amy Reilein, Rachel Misner, Lena Kogan, Tulle Hazelrigg and Iva Greenwald for continued discussions and input, the Bloomington stock center for provision of genetic reagents, the Developmental Studies Hybridoma Bank (DSHB) for antibodies, FlyBase as an information resource, and the confocal microscope resource provided by the Department of Biological Sciences, Columbia University.

1. Received: July 17, 2020
2. Accepted: October 30, 2020
3. Accepted Manuscript published: November 2, 2020 (version 1)
4. Version of Record published: November 27, 2020 (version 2)

© 2020, Melamed and Kalderon

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